Computer-Aided aptamer design for sulfadimethoxine antibiotic: step by step mutation based on MD simulation approach

Based on mutated aptamer-smartphone colorimetric detection of metronidazole in milk

Excessive residue of metronidazole (MNZ) in food is harmful to the human body. There is an urgent demand to develop a portable tool for MNZ detection on-site. In this study, fifteen aptamers were prepared through targeted base mutation. Apt1-3 with the highest enrichment was chosen for further study. Its affinity was characterized by molecular docking simulation, AuNPs colorimetric assay, graphene oxide (GO) fluorescence assay, and exonuclease assay. Kd was determined by GO fluorescence assay (Kd: 92.60 ± 25.59 nM). Its specificity was also characterized by an exonuclease assay. A novel aptasensor was constructed by using the newly identified aptamer combined with the smartphone dark box. The principle of color change is caused by the aggregation state of AuNPs. Smartphones act as reading instruments. The detection can be completed in just a few seconds without the aid of instruments, achieving a detection limit of 0.15 nmol/mL and a range of 6.7-44.4 nmol/mL (R 2 = 0.9810). Therefore, the constructed smartphone colorimetric sensor based on mutant aptamers has important applications in food detection.

Molecular Modeling Methods in the Development of Affine and Specific Protein-Binding Agents

High-affinity and specific agents are widely applied in various areas, including diagnostics, scientific research, and disease therapy (as drugs and drug delivery systems). It takes significant time to develop them. For this reason, development of high-affinity agents extensively utilizes computer methods at various stages for the analysis and modeling of these molecules. The review describes the main affinity and specific agents, such as monoclonal antibodies and their fragments, antibody mimetics, aptamers, and molecularly imprinted polymers. The methods of their obtaining as well as their main advantages and disadvantages are briefly described, with special attention focused on the molecular modeling methods used for their analysis and development.

Toward the Ultimate Limit of Analyte Detection, in Graphene-Based Field-Effect Transistors

The ultimate sensitivity of field-effect-transistor (FET)-based devices for ionic species detection is of great interest, given that such devices are capable of monitoring single-electron-level modulations. It is shown here, from both theoretical and experimental perspectives, that for such ultimate limits to be approached the thermodynamic as well as kinetic characteristics of the (FET surface)-(linker)-(ion-receptor) ensemble must be considered. The sensitivity was probed in terms of optimal packing of the ensemble, through a minimal charge state/capacitance point of view and atomic force microscopy. Through the fine-tuning of the linker and receptor interaction with the sensing surface, a record limit of detection as well as specificity in the femtomolar range, orders of magnitude better than previously obtained and in excellent accord with prediction, was observed.

Prediction of Aptamer-Small-Molecule Interactions Using Metastable States from Multiple Independent Molecular Dynamics Simulations

Understanding aptamer-ligand interactions is necessary to rationally design aptamer-based systems. Commonly used in silico tools have proven to be accurate to predict RNA and DNA oligonucleotide tertiary structures. However, given the complexity of nucleic acids, the most thermodynamically stable conformation is not necessarily the one with the highest affinity for a specific ligand. Because many metastable states may coexist, it remains challenging to predict binding sites through molecular docking simulations using available computational pipelines. In this study, we used independent simulations to broaden the conformational diversity sampled from DNA initial models of distinct stability and assessed the binding affinity of selected metastable representative structures. In our results, utilizing multiple metastable conformations for molecular docking analysis helped identify structures favorable for ligand binding and accurately predict the binding sites. Our workflow was able to correctly identify the binding sites of the characterized adenosine monophosphate and l-argininamide aptamers. Additionally, we demonstrated that our pipeline can be used to aid the design of competition assays that are conducive to aptasensing strategies using an uncharacterized aflatoxin B1 aptamer. We foresee that this approach may help rationally design effective and truncated aptamer sequences interacting with protein biomarkers or small molecules of interest for drug design and sensor applications.

Electrochemical Aptasensors for Antibiotics Detection: Recent Achievements and Applications for Monitoring Food Safety

Antibiotics are often used in human and veterinary medicine for the treatment of bacterial diseases. However, extensive use of antibiotics in agriculture can result in the contamination of common food staples such as milk. Consumption of contaminated products can cause serious illness and a rise in antibiotic resistance. Conventional methods of antibiotics detection such are microbiological assays chromatographic and mass spectroscopy methods are sensitive; however, they require qualified personnel, expensive instruments, and sample pretreatment. Biosensor technology can overcome these drawbacks. This review is focused on the recent achievements in the electrochemical biosensors based on nucleic acid aptamers for antibiotic detection. A brief explanation of conventional methods of antibiotic detection is also provided. The methods of the aptamer selection are explained, together with the approach used for the improvement of aptamer affinity by post-SELEX modification and computer modeling. The substantial focus of this review is on the explanation of the principles of the electrochemical detection of antibiotics by aptasensors and on recent achievements in the development of electrochemical aptasensors. The current trends and problems in practical applications of aptasensors are also discussed.

Insights into glyphosate removal efficiency using a new 2D nanomaterial

Glyphosate (GLY) is a nonselective herbicide that has been widely used in agriculture for weed control. However, there are potential genetic, development and reproduction risks to humans and animals associated with exposure to GLY. Therefore, the removal of this type of environmental pollutants has become a significant challenge. Some of the two-dimensional nanomaterials, due to the characteristics of hydrophilic nature, abundant highly active surficial sites and, large specific surface area are showed high removal efficiency for a wide range of pollutants. The present study focused on the adsorption behavior of GLY on silicene nanosheets (SNS). In order to provide more detailed information about the adsorption mechanism of contaminants on the adsorbent's surface, molecular dynamics (MD) and well-tempered metadynamics simulations are performed. The MD results are demonstrated that the contribution of the L-J term in pollutant/adsorbent interactions is more than coulombic energy. Furthermore, the simulation results demonstrated the lowest total energy value for system-A (with the lowest pollutant concentration), while system-D (contains the highest concentration of GLY) had the most total energy (E tot: -78.96 vs. -448.51 kJ mol-1). The well-tempered metadynamics simulation is accomplished to find the free energy surface of the investigated systems. The free energy calculation for the SNS/GLY system indicates a stable point in which the distance of GLY from the SNS surface is 1.165 nm.

Discovery of the Lead Molecules Targeting the First Step of the Histidine Biosynthesis Pathway of Acinetobacter baumannii

Acinetobacter baumannii is a multidrug-resistant, opportunistic, nosocomial pathogen for which a new line of treatments is desperately needed. We have targeted the enzyme of the first step of the histidine biosynthesis pathway, viz., ATP-phosphoribosyltransferase (ATP-PRT). The three-dimensional structure of ATP-PRT was predicted on the template of the known three-dimensional structure of ATP-PRT from Psychrobacter arcticus (PaATPPRT) using a homology modeling approach. High-throughput virtual screening (HTVS) of the antibacterial library of Life Chemicals Inc., Ontario, Canada was carried out followed by molecular dynamics simulations of the top hit compounds. In silico results were then biochemically validated using surface plasmon resonance spectroscopy. We found that two compounds, namely, F0843-0019 and F0608-0626, were binding with micromolar affinities to the ATP-phosphoribosyltransferase from Acinetobacter baumannii (AbATPPRT). Both of these compounds were binding in the same way as AMP in PaATPPRT, and the important residues of the active site, viz., Val4, Ser72, Thr76, Tyr77, Glu95, Lys134, Val136, and Tyr156, were also interacting via hydrogen bonds. The calculated binding energies of these compounds were -10.5 kcal/mol and -11.1 kcal/mol, respectively. These two compounds can be used as the potential lead molecules for designing antibacterial compounds in the future, and this information will help in drug discovery programs against Acinetobacter worldwide.

Recent advances in computational methods for biosensor design

Biosensors are analytical tools with a great application in healthcare, food quality control, and environmental monitoring. They are of considerable interest to be designed by using cost-effective and efficient approaches. Designing biosensors with improved functionality or application in new target detection has been converted to a fast-growing field of biomedicine and biotechnology branches. Experimental efforts have led to valuable successes in the field of biosensor design; however, some deficiencies restrict their utilization for this purpose. Computational design of biosensors is introduced as a promising key to eliminate the gap. A set of reliable structure prediction of the biosensor segments, their stability, and accurate descriptors of molecular interactions are required to computationally design biosensors. In this review, we provide a comprehensive insight into the progress of computational methods to guide the design and development of biosensors, including molecular dynamics simulation, quantum mechanics calculations, molecular docking, virtual screening, and a combination of them as the hybrid methodologies. By relying on the recent advances in the computational methods, an opportunity emerged for them to be complementary or an alternative to the experimental methods in the field of biosensor design.

Methods and Applications of In Silico Aptamer Design and Modeling

Aptamers are nucleic acid analogues of antibodies with high affinity to different targets, such as cells, viruses, proteins, inorganic materials, and coenzymes. Empirical approaches allow the design of in vitro aptamers that bind particularly to a target molecule with high affinity and selectivity. Theoretical methods allow significant expansion of the possibilities of aptamer design. In this study, we review theoretical and joint theoretical-experimental studies dedicated to aptamer design and modeling. We consider aptamers with different targets, such as proteins, antibiotics, organophosphates, nucleobases, amino acids, and drugs. During nucleic acid modeling and in silico design, a full set of in silico methods can be applied, such as docking, molecular dynamics (MD), and statistical analysis. The typical modeling workflow starts with structure prediction. Then, docking of target and aptamer is performed. Next, MD simulations are performed, which allows for an evaluation of the stability of aptamer/ligand complexes and determination of the binding energies with higher accuracy. Then, aptamer/ligand interactions are analyzed, and mutations of studied aptamers made. Subsequently, the whole procedure of molecular modeling can be reiterated. Thus, the interactions between aptamers and their ligands are complex and difficult to understand using only experimental approaches. Docking and MD are irreplaceable when aptamers are studied in silico.